Feasibility and usefulness of cognitive monitoring using a new home-based cognitive test in mild cognitive impairment: a prospective single arm study
Bibliographic record
Abstract
BACKGROUND: The risk of dementia is increased in subjects with mild cognitive impairment (MCI). Despite the plethora of in-person cognitive tests, those that can be administered over the phone are lacking. We hypothesized that a home-based cognitive test (HCT) using phone calls would be feasible and useful in non-demented elderly. We aimed to assess feasibility and validity of a new HCT as an optional cognitive monitoring tool without visiting hospitals. METHODS: Our study was conducted in a prospective design during 24 weeks. We developed a new HCT consisting of 20 questions (score range 0-30). Participants with MCI (n = 38) were consecutively enrolled and underwent regular HCTs during 24 weeks. Associations between HCT scores and in-person cognitive scores and Alzheimer's disease (AD) biomarkers were evaluated. In addition, HCT scores in MCI participants were cross-sectionally compared with age-matched cognitively normal (n = 30) and mild AD dementia (n = 17) participants for discriminative ability of the HCT. RESULTS: HCT had good intra-class reliability (test-retest Cronbach's alpha 0.839). HCT scores were correlated with the Mini-Mental State Examination (MMSE), verbal memory delayed recall, and Stroop test scores but not associated with AD biomarkers. HCT scores significantly differed among cognitively normal, MCI, and mild dementia participants, indicating its discriminative ability. Finally, 32 MCI participants completed follow-up evaluations, and 8 progressed to dementia. Baseline HCT scores in dementia progressors were lower than those in non-progressors (p = 0.001). CONCLUSION: The feasibility and usefulness of the HCT were demonstrated in elderly subjects with MCI. HCT could be an alternative option to monitor cognitive decline in early stages without dementia.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".